Abstract
The aim of this study was to identify genomic regions underlying milk production traits in the Valle del Belice dairy sheep using regional heritability mapping (RHM). Repeated measurements for milk yield (MY), fat percentage and yield (F% and FY) and protein percentage and yield (P% and PY), collected over a period of 6 years (2006–2012) on 481 Valle del Belice ewes, were used for the analysis. Animals were genotyped with the Illumina 50k SNP chip. Variance components, heritabilities and repeatabilities within and across lactations were estimated, fitting parity, litter size, season of lambing and fortnights in milk, as fixed; and additive genetic, permanent environment within and across lactations, flock by test‐day interaction and residual as random effects. For the RHM analysis, the model included the same fixed and random effects as before, plus an additional regional genomic additive effect (specific for the region being tested) as random. While the whole genomic additive effect was estimated using the genomic relationship matrix (GRM) constructed from all SNPs, the regional genomic additive effect was estimated from a GRM matrix constructed from the SNPs within each region. Heritability estimates ranged between 0.06 and 0.15, with repeatabilities being between 0.14 and 0.24 across lactations and between 0.23 and 0.39 within lactation for all milk production traits. A substantial effect of flock‐test‐day on milk production traits was also estimated. Significant genomic regions at either genome‐wide (p < .05) or suggestive (i.e., one false positive per genome scan) level were identified on chromosome (OAR) 2, 3 and 20 for F% and on OAR3 for P%, with the regions on OAR3 in common between the two traits. Our results confirmed the role of LALBA and AQP genes, on OAR3, as candidate genes for milk production traits in sheep.
Highlights
The Mediterranean Basin countries host approximately 46% of the total world sheep milk production (Carta et al, 2009)
To investigate if the significant single nucleotide polymorphism (SNP) detected in this study mapped within genes or previously reported quantitative trait loci (QTL) for relevant traits, we searched them in NCBI Genome Data Viewer for Ovis aries v4.0 genome assembly and in the SheepQTLdb for milk production QTL, respectively
This study identified marker rs399070200, located in the third intron of this gene, as the SNP with the most highly significant association, detected on OAR3 both for P% and F%
Summary
The Mediterranean Basin countries host approximately 46% of the total world sheep milk production (Carta et al, 2009). The genetic control of complex traits (such as milk production) in livestock has been studied without identifying the genes or gene variants underlying observed variation, with selection on the basis of estimated breeding values calculated from phenotypic and pedigree information (Goddard & Hayes, 2009). One of the shortcomings of a standard GWAS study is the large number of statistical tests performed, which usually requires very stringent thresholds to be applied to avoid spurious associations Such rigorous thresholds minimize false-positive associations and lead to many false negatives since SNPs with small effects or incomplete linkage disequilibrium (LD) with the causative mutation will fail to pass the stringent statistical threshold and remain undetected (Hayes, 2013). The objective of this study was, to identify loci and/or genomic regions affecting milk production traits (i.e., milk yield (MY), fat yield (FY), fat percentage (F%), protein yield (PY) and protein percentage (P%)) in Valle del Belice dairy sheep, using the RHM approach
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